While machine vision has conquered automation, one continuing challenge is accurately reading and processing low-contrast features, especially molded objects, with lettering composed of the same materi- als as the background. For example, a camera reading the molded, black-on-black features on a tire sidewall can require ten seconds to scan the image and another five seconds to process the image data. This is obviously unsuitable for production environments. 2

Several potential solutions exist to improve machine vision capabilities for molded lettering, including improvements to detection algorithms, illumination systems, and cameras and data processing hardware. A potential solution includes the use of structured light (e.g. Kinect systems) to enable 2D cameras to produce 3D vision. Since this requires only 2D cameras and optical processing systems, processing can be performed in less than a second. 3

Technology Reserve’s client seeks expertise in machine vision hardware and optical character recognition algorithms, including variable or structured illumination systems. Solutions must enable sub-second recognition of low-contrast features, and be cost effective for application within industrial production environments.